改进的区间犹豫算子应用于物流企业选择决策

针对现有区间犹豫模糊Hamacher算子存在的缺陷，构建了一种基于改进的区间犹豫模糊Hamacher加权算子的群决策方法。在分析现有区间犹豫模糊Hamacher算子不能满足幂等性的基础上，定义新的区间犹豫模糊Hamacher四则运算；提出两种改进的区间犹豫模糊Hamacher加权算子，包括改进的区间犹豫模糊Hamacher有序加权平均（I-IVHFHOWA）算子和改进的区间犹豫模糊Hamacher有序加权几何（I-IVHFHOWG）算子，并详细探究它们的常用算子形式以及算子之间的内在联系；建立基于I-IVHFHOWA算子和I-IVHFHOWG算子的物流企业选择决策模型，并通过实例说明模型的有效性。     

The location and sizing of urban freight loading/unloading lay-by areas

The volume of freight vehicles operating within city boundaries is steadily increasing, which contributes to road congestion, especially in urban areas with a parking deficit. The proper identification of the location and size of commercial parking lay-by areas, where delivery vehicles can park for a limited time to perform loading/unloading operations, can relieve road congestion. Compared to the existing literature, this paper presents an improved two-stage approach, which includes a mathematical programme and a simulation model for determining the location and sizing of lay-by areas. The robustness and soundness of the results from a methodological and practical point of view are discussed using an example application.     

改进BP神经网络的再生粗骨料混凝土强度预测*

抗压强度作为评价再生混凝土主要性能指标之一,从四篇文献中搜集了43个抗压强度样本。基于改进的BP神经网络理论,建立了以再生粗骨料取代率、水灰比、龄期为输入,抗压强度为输出的神经网络模型,其结构形式为3-7-9-1。对该网络进行训练和学习,对并测试样本进行检测,结果表明,训练效率不仅大大提高,且而误差较小,并结合回归拟合系数,进一步表明该模型能够有效的的预测再生混凝土抗压强度值,能满足工程需要。     

生鲜果蔬物流及包装技术研究与展望

生鲜果蔬是人们膳食结构的基本组成，在国民经济发展中占有重要的战略地位。然而，生鲜果蔬在物流过程中存在保质期短、营养流失严重等难题，难以满足产业快速发展及人们对高品质生活的需求。作者从生鲜果蔬动态物流保鲜的视角，从采后预冷技术、物流包装材料与技术、蓄冷与保温技术、物流过程品质监测技术等方面，全面综述了国内外生鲜果蔬物流及包装技术的研究现状和科技前沿，并对未来的研究趋势进行了展望，旨为生鲜果蔬物流与包装技术的科技创新和产业发展提供参考。     

Integration of AHP-TOPSIS method for prioritizing the solutions of reverse logistics adoption to overcome its barriers under fuzzy environment

Reverse logistics practices are gaining attention due to industrial ecology, enforced legislation and corporate citizenship but presence of barriers make reverse logistics (RL) implementation difficult and hence reduce the success rate. To increase RL adoption, robust and flexible strategies are required to overcome its barriers. This study focuses on identification and ranking the solutions of reverse logistics adoption in electronics industry to overcome its barriers. It aids firms to ponder on high rank solutions and develop strategies to implement them on priority. This paper proposes a methodology based on fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to identify and rank the solutions of RL adoption to overcome its barriers. Fuzzy AHP is applied to get weights of the barriers as criteria by pairwise comparison and final ranking of the solutions of RL adoption is obtained through fuzzy TOPSIS. The empirical case of Indian electronics industry is shown to illustrate the use of the proposed method. This proposed method offers a more precise, efficient and effective decision support tool for stepwise implementation of the solutions due to consideration of fuzzy environment. Finally sensitivity analysis is performed to illustrate the robustness of the method.     

Decision evaluation process in end-of-life systems management

In manufacturing sectors, firms are paying an increasing attention to sustainability concept with regard to their end-of-life products in order to respect environmental norms and satisfy the consumer sensitivity. This practise allows creating value by reintroducing dismantling and recovering parts and/or materials of end-of-life products into manufacturing process, or into maintenance process. Thus, deconstruction processes are developed in order to examine all activities addressing the end of life (EOL) systems to ensure its disposal according to environmental constraints when seeking an economic optimum. In this context, one of the first tasks to perform is to repatriate the EOL systems at lowest cost considering geographical optimization of treatment centers. Considering this point, the present paper proposes an evaluation and optimization approach for the withdrawal location process in the field of aircraft dismantling. Given the multitude and heterogeneity of characteristics to be taken into account, we propose to consider dismantling site location problem as multi-criteria/multi-objectives decision making problem and solve it using a new AHP-BOCR approach based on qualitative and quantitative evaluations. A bipolar structuring framework is considered to distinguish positive and negative aspects in the elicitation/evaluation process to avoid compensation and satisficing game theory is used as suitable mathematical tool for recommendation process. An experimental study is carried out to show the usefulness of the framework.     

落后产能炼油企业向物流行业转型研究

落后产能炼油企业成本偏高、市场竞争能力不强,面临紧迫的转型压力。本文基于炼油企业的资源优势、市场需求、政策导向、财务效益等因素,根据企业转型战略要求和目标,分析落后产能炼油企业向物流行业转型的可行性和转型路径。     

Multi-objective particle swarm optimisation based integrated production inventory routing planning for efficient perishable food logistics operations

Sustainable and efficient food supply chain has become an essential component of one’s life. The model proposed in this paper is deeply linked to people's quality of life as a result of which there is a large incentive to fulfil customer demands through it. This proposed model can enhance food quality by making the best possible food quality accessible to customers, construct a sustainable logistics system considering its environmental impact and ensure the customer demand to be fulfilled as fast as possible. In this paper, an extended model is examined that builds a unified planning problem for efficient food logistics operations where four important objectives are viewed: minimising the total expense of the system, maximising the average food quality along with the minimisation of the amount of CO₂ emissions in transportation along with production and total weighted delivery lead time minimisation. A four objective mixed integer linear programming model for intelligent food logistics system is developed in the paper. The optimisation of the formulated mathematical model is proposed using a modified multi-objective particle swarm optimisation algorithm with multiple social structures: MO-GLNPSO (Multi-Objective Global Local Near-Neighbour Particle Swarm Optimisation). Computational results of a case study on a given dataset as well as on multiple small, medium and large-scale datasets followed by sensitivity analysis show the potency and effectiveness of the introduced method. Lastly, there has been a scope for future study displayed which would lead to the further progress of these types of models.     

Designing a closed-loop supply chain network for citrus fruits crates considering environmental and economic issues

Most cities, notably major and agricultural ones, are faced with environmental and waste problems. Distribution and collection of agricultural crops can be challenging duties as world demand and production are substantially increased. Accordingly, resource depletion, environmental concern, and the importance of the circular economy have convinced this research group to focus on a Closed-Loop Supply Chain (CLSC) network design. In this study, a new mixed linear mathematical model for a CLSC was developed which minimizes the CLSC’s total costs and which tackles and controls air pollution. Contrary to previous works about supply chain network design, we firstly consider citrus fruits’ crates in our model. To solve the model, two leading algorithms, Genetic Algorithm and Simulated Annealing, are employed and a third recently successful method, Keshtel Algorithm, is utilized. Further, two hybridization algorithms stemmed from mentioned ones are applied. Finally, the results are assessed by different criteria and compared, and then the two best algorithms are chosen in this case. Consequently, in order to achieve the most effective result, a real case study of crates was conducted. The results obviously presented applicability and efficiency of the proposed model. Thus, the most suitable network for CLSC of citrus fruits’ crates was designed in which the costs and emissions were reduced.     

An adaptive local search algorithm for vehicle routing problem with simultaneous and mixed pickups and deliveries

The Vehicle Routing Problem with Simultaneous Pickup and Delivery (VRPSPD) is an extension to the classical Vehicle Routing Problem (VRP), where customers may both receive and send goods simultaneously. The Vehicle Routing Problem with Mixed Pickup and Delivery (VRPMPD) differs from the VRPSPD in that the customers may have either pickup or delivery demand. However, the solution approaches proposed for the VRPSPD can be directly applied to the VRPMPD. In this study, an adaptive local search solution approach is developed for both the VRPSPD and the VRPMPD, which hybridizes a Simulated Annealing inspired algorithm with Variable Neighborhood Descent. The algorithm uses an adaptive threshold function that makes the algorithm self-tuning. The proposed approach is tested on well-known VRPSPD and VRPMPD benchmark instances derived from the literature. The computational results indicate that the proposed algorithm is effective in solving the problems in reasonable computation time.